All workshops will take place on Saturday in YeungNam University, GyeongSan, South Korea. Workshop can be cancelled if the total number of people who register is less than 20. There are desktop computers with Internet connections. However, all the participants are supposed to bring their own laptop computers.
★Workshop 1 / Big Data Analytics using Textom, NodeXL KrKwic, and Webometric 2.0
Date & Time : >Saturday, 13 December / 09:00~12:00
Venue : Room No. 302, 2nd Humanities Building, YeungNam University
Organizers: Chae Nam Chon (The IMC), In Ho Cho (The IMC), Ji-Won Park (YeungNam Univ.), Han Woo Park (YeungNam Univ.)
This workshop will provide an interactive training session on how researchers in humanities and social sciences can employ Big Data Analytics tools to explore cultural activities on social media sphere (e.g., Naver, Facebook, Twitter, YouTube). This workshop begins with the introduction of Big Data Metrics. Next, it will introduce participants to the practices of data collection and organization procedures for your own research. Among several popular tools, Textom and NodeXL have increasingly been used for tracking online actions in everyday life. Therefore, this workshop uses both sofwares as primary tools.
★Workshop 2 / Analyzing Words and Networks with ConText
Date & Time : Saturday, 13 December / 14:00~18:00
Venue : Room No. 302, 2nd Humanities Building, YeungNam University
Organizers: Jana Diesner, Jinseok Kim
Language: English (Korean supported)
The functioning and dynamics of real-world networks involve the continuous production, processing and flow of knowledge and information. Sources for this knowledge and information often occur in the form of unstructured, natural language text data. In this workshop, participants learn how to a) construct network data from text data and pertaining meta-data, and b) how to jointly consider text data and network data for analysis. Using text analysis for network analysis has been useful in answering questions such as: Who is talking to whom, and about what? What perceptions or mental models do social agents have of certain themes? How do opinions evolve and diffuse in society and online? Throughout this workshop, we discuss practical applications for the introduced techniques from various domains. Attendants will learn practical, hands-on skills for using text analysis methods with ConText software.
Extended Information on Workshop
Workshop: Analyzing Words and Networks with ConText Information and Relation Extraction from Text Data, Network Visualization and Analysis
Instructors: JanaDiesner,PhD(http://people.lis.illinois.edu/~jdiesner/), Jinseok Kim
1. What is covered in the workshop? What will you learn?
The functioning and dynamics of real-world networks involve the continuous production, processing and flow of knowledge and information. Sources for this knowledge and information often occur in the form of unstructured, natural language text data. In this workshop, participants learn how to a) construct network data from text data and pertaining meta-data, and b) how to jointly consider text data and network data for analysis; allowing for considering two types of behavioral information, namely social interactions and language use.
Workshop participants are introduced to fundamental theories, concepts and methods for these purposes. Using text analysis for network analysis has been useful in answering questions such as: Who is talking to whom, and about what? What perceptions or mental models do social agents have of certain themes? How do opinions evolve and diffuse in society and online? Throughout this workshop, we discuss practical applications for the introduced techniques from various domains.
The focus of this workshop is on teaching practical, hands-on skills for using text analysis methods in an informed, systematic and efficient fashion. We use the ConText software. Our goal is to equip the participants with the skills and tools needed to use the covered techniques for their own research purposes and text data sets. Attendants will perform automated text mining and natural language processing techniques including:
Going from texts to networks involves some principles and strategies originating from computer science that are not only applicable to the task at hand, but to a wide range of problems. These principles and strategies are referred to as “Computational Thinking” – a basic skill like reading, writing and arithmetic that is crucial for solving problems and understanding human behavior across fields (Wing 2006). In this workshop, participants are introduced to Computational Thinking and practice applying this way of thinking.
2. Who should attend?
This is an interdisciplinary and interactive workshop designed to benefit from the participation of attendants from different backgrounds. The material, exercises and mode of delivery are suitable for researchers and practitioners alike. No specific prior knowledge or computational skills are required. The delivery is driven towards forming an understanding of fundamental concepts and gaining hands-on experience with text analysis and network analysis methods and tools.
3. What to bring to the workshop?
Software: We will use ConText (http://context.lis.illinois.edu/) and Gephi (https://gephi.org) for this workshop. Prior to the workshop, I will send an email to confirmed participants with links and installation instructions for these tools. You are invited to bring a laptop to the workshop. If attendants cannot bring a laptop they will still fully benefit from the workshop as I screen-project all live walk-through exercises. At the workshop, I will provide a tutorial document and further learning resources. Data: Attendants can work with the sample data that we provide and/ or bring their own data.
Prior to the workshop, I recommend reading the following overviews on the concepts and methods covered in the workshop:
- Diesner, J., Carley, K. M. (2011): Semantic Networks. In G. Barnett (Ed), Encyclopedia of Social Networking, (pp. 595-598). Sage Publications. http://people.lis.illinois.edu/~jdiesner/publications/Semantic_Networks_Diesner_Carley_2011.pdf
- Diesner, J., Carley, K. M. (2011): Words and Networks. In G. Barnett (Ed.), Encyclopedia of Social Networking, (pp. 958-961). Sage Publications. http://people.lis.illinois.edu/~jdiesner/publications/Word_Networks_Diesner_carley_2011.pdf
All further readings are optional:
- Introduction of information extraction/ text mining: McCallum, A. (2005). Information extraction: distilling structured data from unstructured text. ACM Queue, 3(9), 48-57.
- Introduction of information extraction/ text mining: Hanneman, RA & Riddle, M. (2005). Introduction to social network methods. Riverside, CA: University of California.
- Introduction to Computational Thinking: Wing, J. M. (2006). Computational Thinking. Communications of the ACM, 49(3), 33-35,http://dl.acm.org/citation.cfm?id=1118215
5. Information about the instructors
Jana Diesner is an Assistant Professor at the iSchool (a.k.a. Graduate School of Library and Information Science) at the University of Illinois Urbana-Champaign (UIUC), and an affiliate at the Department of Computer Science (CS). She got her PhD from Carnegie Mellon University, School of Computer Science. Jana’s work is at the nexus of social network analysis, natural language processing and machine learning. With her team, Jana is developing and advancing computational methods and technologies that help people to measure and understand the interplay and co-evolution of information and socio-technical networks. She brings these computational solutions into various application context, currently mainly in the domains of medical informatics and media impact assessment. For more information about Jana’s work see http://people.lis.illinois.edu/~jdiesner/.
Contact Jana with any questions about the workshop at email@example.com.